Evidence map›Paper›PMID 24228698›Full record

ArticleBMC medicine2013

OMICS-based personalized oncology: if it is worth doing, it is worth doing well!

Daniel F Hayes

Open access · goldAbstract readComment
In one paragraph

Article in BMC medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.5field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 20 citations in OpenAlex.

  1. Omics Profiling in Precision Oncology.Molecular & cellular proteomics : MCP · 2016
    Review
  2. Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Daniel F HayesBreast Oncology Program, University of Michigan Comprehensive Cancer Center, 6312 Cancer Center, 1500 E, Medical Center Drive, Ann Arbor, MI 48109-0942, USA. hayesdf@umich.edu.
Michigan Center for Translational Pathology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The era of Personalized Medicine implies getting the right treatment to the right patient at the right schedule and dose at the right time. Tumor biomarker tests are keys to accomplishing this goal successfully. However, much of the translational research regarding tumor biomarker tests has been haphazard, often using data and specimen sets of convenience and ignoring many of the principles of the scientific method. In papers published simultaneously in BMC Medicine and Nature, McShane and colleagues have proposed a checklist of criteria that should be followed by investigators planning to conduct prospective clinical trials directed towards generating high levels of evidence to demonstrate whether a tumor biomarker test has clinical utility for a specific context. These criteria were generated in response to a roadmap reported by a committee convened by the U.S. Institute of Medicine for generation of omics-based biomarker tests. Taken together with several other initiatives to increase the rigor of tumor biomarker research, these criteria will increase the perception of value for tumor biomarker test research and application in the clinic. Please see related article: http://www.biomedcentral.com/1741-7015/11/220.

Indexed as

Clinical Trials as TopicGenomicsHumans

Identifiers

PMID24228698
PMCPMC3876724
OpenAlexW1989165146

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.